Methods and system for shading a two-dimensional ultrasound image

ABSTRACT

Various methods and systems are provided for shading a 2D ultrasound image, generated from ultrasound data, using a gradient determined from scalar values of the ultrasound image data. As one example, a method includes correlating image values of a dataset acquired with an ultrasound imaging system to height values; determining a gradient of the height values; applying shading to a 2D image generated from the dataset using the determined gradient; and displaying the shaded 2D image.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. Non-Provisional patentapplication Ser. No. 15/587,733, entitled “METHODS AND SYSTEM FORSHADING A TWO-DIMENSIONAL ULTRASOUND IMAGE”, filed on May 5, 2017. Theentire contents of the above-listed application are incorporated hereinby reference for all purposes.

FIELD

Embodiments of the subject matter disclosed herein relate to applyingshading to a two-dimensional ultrasound image.

BACKGROUND

An ultrasound imaging system may be used to acquire images of apatient's anatomy. Ultrasound imaging systems may acquire a datasetwhich is then used to generate a 2D image that a medical professionalmay view and use to diagnose a patient. However, the dataset may include2D scalar data (e.g., intensity values, power component values, or thelike) which results in a flat 2D image that may be more difficult tointerpret, thereby increasing a difficulty of diagnosing a patient usingthe flat 2D image. For example, more complex body structures may bedifficult to recognize via a 2D image. As one example, 2D color Dopplerimages of different body structures may be especially difficult to usefor diagnosis.

BRIEF DESCRIPTION

In one embodiment, a method comprises correlating image values of adataset acquired with an ultrasound imaging system to height values;determining a gradient of the height values; applying shading to a 2Dimage generated from the dataset using the determined gradient; anddisplaying the shaded 2D image.

It should be understood that the brief description above is provided tointroduce in simplified form a selection of concepts that are furtherdescribed in the detailed description. It is not meant to identify keyor essential features of the claimed subject matter, the scope of whichis defined uniquely by the claims that follow the detailed description.Furthermore, the claimed subject matter is not limited toimplementations that solve any disadvantages noted above or in any partof this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

The present invention will be better understood from reading thefollowing description of non-limiting embodiments, with reference to theattached drawings, wherein below:

FIG. 1 shows an ultrasound imaging system according to an embodiment ofthe invention.

FIG. 2 shows an example of an unshaded 2D ultrasound image generatedfrom an imaging dataset, and additionally shows a shaded 2D ultrasoundimage generated from the imaging dataset, according to an embodiment ofthe invention.

FIG. 3 shows a flow chart of a method for shading a 2D ultrasound image,generated from an ultrasound dataset, using a gradient determined fromscalar values of the ultrasound image dataset, according to anembodiment of the invention.

FIG. 4 shows an example of an unshaded 2D Doppler ultrasound imagegenerated from an imaging dataset, according to an embodiment of theinvention.

FIG. 5 shows an example of a shaded 2D Doppler ultrasound imagegenerated from an imaging dataset, according to an embodiment of theinvention.

FIG. 6 shows an example of an unshaded 2D B-mode ultrasound imagegenerated from an imaging dataset, according to an embodiment of theinvention.

FIG. 7 shows an example of a shaded 2D B-mode ultrasound image generatedfrom an imaging dataset, according to an embodiment of the invention.

DETAILED DESCRIPTION

The following description relates to various embodiments of shading a 2Dultrasound image using a gradient determined from height valuescorrelated to image values of an ultrasound imaging dataset (which maybe 1D, 2D, or 3D) used to generate the 2D ultrasound image. Anultrasound system, such as the system shown in FIG. 1, may be used toacquire the ultrasound imaging dataset. A 2D image may then be generatedusing the acquired dataset. An example of a 2D ultrasound imagegenerated from an imaging dataset is shown in FIG. 2. FIG. 2 also showsan example of a shaded 2D ultrasound image where the shading is appliedto the 2D ultrasound image using a gradient surface normal determinedfrom image values of the dataset that have been converted to heightvalues. For example, as shown by the method of FIG. 3, image values,such as power or intensity values, of an acquired ultrasound imagingdataset may be converted to height values. A gradient is then determinedfor the converted height values and shading is applied to the 2D imageusing the determined gradient. Examples showing a difference betweenunshaded 2D ultrasound images and shaded 2D ultrasound images (using themethod of FIG. 3) are shown by FIGS. 4-7. For example, FIG. 4 shows afirst unshaded 2D ultrasound image which may be compared to a firstshaded 2D ultrasound image shown by FIG. 5, and FIG. 6 shows a secondunshaded 2D ultrasound image which may be compared to a second shaded 2Dultrasound image shown by FIG. 7. In this way, a resulting shaded 2Dultrasound image may have the appearance of depth, thereby making theresulting shaded 2D ultrasound image easier to interpret and, thus, usedfor patient diagnosis.

Turning now to FIG. 1, a schematic diagram of an ultrasound imagingsystem 100 in accordance with an embodiment of the invention is seen.The ultrasound imaging system 100 includes a transmit beamformer 101 anda transmitter 102 that drives elements 104 within a transducer array,herein referred to as probe 106, to emit pulsed ultrasonic signals intoa body (not shown). According to an embodiment, the probe 106 may be aone-dimensional transducer array probe. However, in some embodiments,the probe 106 may be a two-dimensional matrix transducer array probe.After the elements 104 of the probe 106 emit pulsed ultrasonic signalsinto a body (of a patient), the pulsed ultrasonic signals areback-scattered from structures within an interior of the body, likeblood cells or muscular tissue, to produce echoes that return to theelements 104. The echoes are converted into electrical signals, orultrasound data, by the elements 104 and the electrical signals arereceived by a receiver 108. The electrical signals representing thereceived echoes are passed through a receive beamformer 110 that outputsultrasound data. According to some embodiments, the probe 106 maycontain electronic circuitry to do all or part of the transmitbeamforming and/or the receive beamforming. For example, all or part ofthe transmit beamformer 101, the transmitter 102, the receiver 108, andthe receive beamformer 110 may be situated within the probe 106. Theterms “scan” or “scanning” may also be used in this disclosure to referto acquiring data through the process of transmitting and receivingultrasonic signals. The term “data” may be used in this disclosure torefer to either one or more datasets acquired with an ultrasound imagingsystem. A user interface 115 may be used to control operation of theultrasound imaging system 100, including to control the input of patientdata (e.g., patient medical history), to change a scanning or displayparameter, and the like. The user interface 115 may include one or moreof the following: a rotary, a mouse, a keyboard, a trackball, hard keyslinked to specific actions, soft keys that may be configured to controldifferent functions, and a graphical user interface displayed on adisplay device 118.

The ultrasound imaging system 100 also includes a processor 116 tocontrol the transmit beamformer 101, the transmitter 102, the receiver108, and the receive beamformer 110. The processor 116 is in electroniccommunication (e.g., communicatively connected) with the probe 106. Forpurposes of this disclosure, the term “electronic communication” may bedefined to include both wired and wireless communications. The processor116 may control the probe 106 to acquire data. The processor 116controls which of the elements 104 are active and the shape of a beamemitted from the probe 106. The processor 116 is also in electroniccommunication with the display device 118, and the processor 116 mayprocess the data (e.g., ultrasound data) into images for display on thedisplay device 118. The processor 116 may include a central processor(CPU), according to an embodiment. According to other embodiments, theprocessor 116 may include other electronic components capable ofcarrying out processing functions, such as a digital signal processor, afield-programmable gate array (FPGA), or a graphic board. According toother embodiments, the processor 116 may include multiple electroniccomponents capable of carrying out processing functions. For example,the processor 116 may include two or more electronic components selectedfrom a list of electronic components including: a central processor, adigital signal processor, a field-programmable gate array, and a graphicboard. According to another embodiment, the processor 116 may alsoinclude a complex demodulator (not shown) that demodulates the RF dataand generates raw data. In another embodiment, the demodulation can becarried out earlier in the processing chain. The processor 116 isadapted to perform one or more processing operations according to aplurality of selectable ultrasound modalities on the data. In oneexample, the data may be processed in real-time during a scanningsession as the echo signals are received by receiver 108 and transmittedto processor 116. For the purposes of this disclosure, the term“real-time” is defined to include a procedure that is performed withoutany intentional delay. For example, an embodiment may acquire images ata real-time rate of 7-20 frames/sec. The ultrasound imaging system 100may acquire 2D data of one or more planes at a significantly fasterrate. However, it should be understood that the real-time frame-rate maybe dependent on the length of time that it takes to acquire each frameof data for display. Accordingly, when acquiring a relatively largeamount of data, the real-time frame-rate may be slower. Thus, someembodiments may have real-time frame-rates that are considerably fasterthan 20 frames/sec while other embodiments may have real-timeframe-rates slower than 7 frames/sec. The data may be stored temporarilyin a buffer (not shown) during a scanning session and processed in lessthan real-time in a live or off-line operation. Some embodiments of theinvention may include multiple processors (not shown) to handle theprocessing tasks that are handled by processor 116 according to theexemplary embodiment described hereinabove. For example, a firstprocessor may be utilized to demodulate and decimate the RF signal whilea second processor may be used to further process the data prior todisplaying an image. It should be appreciated that other embodiments mayuse a different arrangement of processors.

The ultrasound imaging system 100 may continuously acquire data at aframe-rate of, for example, 10 Hz to 30 Hz (e.g., 10 to 30 frames persecond). Images generated from the data may be refreshed at a similarframe-rate on display device 118. Other embodiments may acquire anddisplay data at different rates. For example, some embodiments mayacquire data at a frame-rate of less than 10 Hz or greater than 30 Hzdepending on the size of the frame and the intended application. Amemory 120 is included for storing processed frames of acquired data. Inan exemplary embodiment, the memory 120 is of sufficient capacity tostore at least several seconds worth of frames of ultrasound data. Theframes of data are stored in a manner to facilitate retrieval thereofaccording to its order or time of acquisition. The memory 120 maycomprise any known data storage medium.

In various embodiments of the present invention, data may be processedin different mode-related modules by the processor 116 (e.g., B-mode,Color Doppler, M-mode, Color M-mode, spectral Doppler, Elastography,TVI, strain, strain rate, and the like) to form 2D or 3D data. Forexample, one or more modules may generate B-mode, color Doppler, M-mode,color M-mode, spectral Doppler, Elastography, TVI, strain, strain rate,and combinations thereof, and the like. As one example, the one or moremodules may process color Doppler data, which may include traditionalcolor flow Doppler, power Doppler, HD flow, and the like. The imagelines and/or frames are stored in memory and may include timinginformation indicating a time at which the image lines and/or frameswere stored in memory. The modules may include, for example, a scanconversion module to perform scan conversion operations to convert theacquired images from beam space coordinates to display spacecoordinates. A video processor module may be provided that reads theacquired images from a memory and displays an image in real time while aprocedure (e.g., ultrasound imaging) is being performed on a patient.The video processor module may include a separate image memory, and theultrasound images may be written to the image memory in order to be readand displayed by display device 118.

In various embodiments of the present invention, one or more componentsof ultrasound imaging system 100 may be included in a portable, handheldultrasound imaging device. For example, display device 118 and userinterface 115 may be integrated into an exterior surface of the handheldultrasound imaging device, which may further contain processor 116 andmemory 120. Probe 106 may comprise a handheld probe in electroniccommunication with the handheld ultrasound imaging device to collect rawultrasound data. Transmit beamformer 101, transmitter 102, receiver 108,and receive beamformer 110 may be included in the same or differentportions of the ultrasound imaging system 100. For example, transmitbeamformer 101, transmitter 102, receiver 108, and receive beamformer110 may be included in the handheld ultrasound imaging device, theprobe, and combinations thereof.

As explained above, in one example, the ultrasound imaging system 100may be used to acquire an ultrasound imaging dataset (e.g., data). Theimaging dataset may include image data, such as intensity data (forB-mode), color or power data (for color Doppler), or the like. Forexample, an imaging dataset acquired via a color Doppler ultrasound mode(such as color Doppler, power Doppler, Turbulence, Velocity-Power, andVelocity-Turbulence modes) may contain color Doppler data that has apower component. In one example, the imaging dataset may be a 2D dataset(e.g., B-mode data). In another example, the imaging dataset may be a 1Ddataset (e.g., motion mode). In yet another example, the imaging datasetmay be a 3D/4D dataset (e.g., 3D dataset with an image plane created byslicing through the volume). The processor 116 may generate a 2Dultrasound image from the acquired imaging dataset. For example, theprocessor 116 may convert the image data of the imaging dataset tobrightness (e.g., intensity) values and display an ultrasound image ofthe acquired dataset as a 2D B-mode image. In another example, theprocessor 116 may convert the image data of the imaging dataset to colorvalues having a power component and display an ultrasound image of theacquired dataset as a 2D color Doppler image. As explained further belowwith reference to FIG. 2, the ultrasound image (e.g., 2D color Dopplerimage, 2D B-mode image, and the like) is comprised of a plurality ofpixels, where each pixel is assigned an image value, such as anintensity or color (e.g., power) value. Each value for each pixel isthen displayed to form the ultrasound image.

FIG. 2 shows an example of a 2D ultrasound image 200 generated from animaging dataset acquired with an ultrasound imaging system (such asultrasound imaging system 100 shown in FIG. 1) and a shaded 2Dultrasound image 202. The 2D ultrasound image 200 includes a pluralityof pixels 204 (e.g., each box in images 200 and 202 represents a pixel).The pixels may be of a display screen (e.g., such as display device 118shown in FIG. 1) which is used to display the 2D ultrasound image 200and/or the shaded 2D ultrasound image 202. As shown in the 2D ultrasoundimage 200, the pixels are displayed on a grid having an x-axis(horizontal) and a y-axis (vertical), where each pixel comprises one xunit along the x-axis and one y unit along the y-axis. Thus, each pixelhas an x and y value defining its position on the grid. Each pixel ofthe 2D ultrasound image 200 is assigned an image value (from theacquired imaging dataset). The image value may be a scalar value such asan intensity value (for b-mode images) or a power value (for Dopplerimages). These image values are represented as a scalar value function,f(x,y), in FIG. 2.

As explained further below, each image value, f(x,y), may be correlatedto a height value, h(x,y). Specifically, each image value at each pixel204 may be converted to a corresponding height value using arelationship (e.g., model). In one example, the relationship forconverting each image value to a height value may be a linearrelationship. In another example, the relationship or model forconverting each image value to a height value may be a monotonicfunction, such as a logarithmic or sigmoid function that is a functionof the image value and then outputs a height value. In some embodiments,the height values (h(x,y), h(x+1, y), etc.) may be used to create aheight map or relief image that represents a height field of the 2Dimage. In this way, the image values may be represented as heightvalues. A gradient may then be calculated for each height value, h(x,y),at each pixel 204.

An example equation for computing the gradient, including a surfacenormal, is shown by Equation 1:

${\overset{->}{n}\left( {x,y} \right)} = {{{\nabla{h\left( {x,y} \right)}}} = {{\begin{pmatrix}\frac{\partial h}{\partial x} \\\frac{\partial h}{\partial y} \\r\end{pmatrix}} = {\begin{pmatrix}{{h\left( {{x - 1},y} \right)} - {h\left( {{x + 1},y} \right)}} \\{{h\left( {x,{y - 1}} \right)} - {h\left( {x,{y + 1}} \right)}} \\r\end{pmatrix}}}}$

In Equation 1, n(x,y) is the surface normal vector at position (x,y)with unit length, ∇ is the gradient, h(x,y) is the scalar height valuefunction (which represents a scalar valued function, such as b-modeintensity, dopper power, or the like) at position (x,y), and r is aconstant defining the roughness of the resulting gradient field. Thenormal of the height value h(x,y) at the position (x,y) is computed bycomputing the norm of the gradient at this position. The gradient isdefined by the partial derivatives in the direction of x and y. The xcomponent is computed with central differences in the x direction. The ycomponent is computed with central differences in the y direction. The zcomponent is the constant r. In this way, determining a gradient foreach height value h(x,y) is based on a difference in height values ofadjacent pixels 204 in the 2D image 200 (e.g., h(x−1,y), h(x+1,y),h(x,y−1), and h(x,y+1)).

In computing the norm (length=1) of the gradient, the influences of theroughness constant varies for different gradient lengths. For example,if the position (x,y) is in a homogenous region (e.g., a region of theimage with little or no variation between height values of adjacentpixels), the x,y components of the gradient are smaller and r is thedominating factor, thereby resulting in a normal vector pointingapproximately in the z direction n=(0,0,1). In another example, if theposition (x,y) is in a greatly varying area (e.g., a region of the imagewith larger variation between height values of adjacent pixels), the xand/or the y component of the gradient is bigger and r has lessinfluence, thereby resulting in the normal pointing slightly upwards inthe direction of the change. As one example, by representing the imagevalues as height values, computing the gradient of the 2D image includescomputing the surface normal of the height field consisting of theheight values.

As shown at 206 in FIG. 2, after computing the gradient of each heightvalue, h(x,y), shading (e.g., surface shading) is applied to the 2Dultrasound image 200 using the surface normal vector, n(x,y), at eachposition (x,y) of the 2D ultrasound image 200. After the application ofsurface shading using the gradient, the resulting image is the shaded 2Dultrasound image 202 which includes shading 208 at each pixel. Theshading model used at 206 may be one or more standard shading models,such as a diffuse specular shading model, a Phong reflection model, aBlinn-Phong shading model, a specular highlight shading model, or thelike. As one example, the Phong reflection model (also referred to asPhong illumination, Phong lighting, or Phong shading) is a model of thelocal illumination of points on a surface (e.g., pixels on the 2Dimage). The Phong reflection model describes the way a surface reflectslight as a combination of the diffuse reflection of rough surfaces withthe specular reflection of shiny surfaces. The model also includes anambient term to account for the small amount of light that is scatteredabout the entire scene.

FIG. 3 shows a flow chart of a method 300 for shading a 2D ultrasoundimage (such as 2D ultrasound image 200 shown in FIG. 2), generated fromultrasound data, using a gradient determined from scalar values of theultrasound image data. Instructions for carrying out method 300 may beexecuted by a processor (such as processor 116 shown in FIG. 1) based oninstructions stored on a memory of the processor (or instructions storedin a memory 120 coupled to processor 116, as shown in FIG. 1) and inconjunction with data received from an imaging system or imaging probe,such as probe 106 described above with reference to FIG. 1. Theprocessor may employ a display device (such as display device 118 shownin FIG. 1) to display a shaded 2D ultrasound image, according to themethods described below.

At 302, the method includes accessing ultrasound data, either previouslyor currently acquired via an ultrasound probe (such as probe 106 shownin FIG. 1) and generating a 2D ultrasound image from the accessedultrasound data. In one embodiment, the processor of the ultrasoundimaging system (such as processor 116 shown in FIG. 1) accesses anultrasound imaging dataset (which may be 1D, 2D, or 3D) that is storedin a memory (such as the memory 120 shown in FIG. 1) of the ultrasoundimaging system. In another embodiment, the ultrasound data may beaccessed in real-time as the data is acquired by the ultrasound probe(e.g., probe 106 shown in FIG. 1). The ultrasound dataset may includeimage data which includes image values, such as intensity values forB-mode ultrasound or power values (or a power component) for Dopplermode ultrasound. A 2D image may then be generated from the accessed(and/or acquired) ultrasound imaging dataset. As described above withreference to FIG. 2, the 2D image generated from the ultrasound imagingdataset (such as image 200 shown in FIG. 2) may be a flat 2D image.

At 304, the method includes selecting a portion of the 2D image desiredfor shading (e.g., relief shading). As one example, for a Doppler 2Dimage, selecting the portion of the 2D image desired for shading mayinclude selecting the color portion (e.g., representing blood flow) ofthe 2D image. As another example, selecting the portion of the 2D imagedesired for shading may include selecting an entirety of the 2D image(e.g., such as selecting an entire area of a 2D B-mode image). Afterselecting the desired portion of the 2D image for shading, the methodmay optionally continue to 306 to filter the image values of the 2Dimage. For example, the method at 306 may include having the processorapply a filter to the image values for each pixel in order to smooth theappearance of the 2D image. In some embodiments, filtering of the imagevalues may not be performed and method 300 may instead proceed directlyfrom 304 to 308.

At 308, the method includes interpreting the 2D image data as a reliefimage (e.g., height map) by correlating the image values of the 2D imageto height values. For example, the processor of the ultrasound imagingsystem may convert the image values of the imaging dataset to heightvalues. As explained above with reference to FIG. 2, each pixel of the2D image may include an image value, such as an intensity value or apower value (or component). In alternate embodiments, the image valuemay include a speed value, a brightness value (which may be convertedfrom a color value), an amplitude value, an elasticity value, or thelike. Each image value for each pixel may be converted to a height valueto create a virtual (e.g., stored in the memory or the processor) heightmap (e.g., relief image). As one embodiment, the processor may convertthe image values for each pixel of the 2D image to height values via amodel or relationship stored in the memory of the ultrasound imagingsystem. For example, the height values may be proportional to imagevalues according to a constant term. In another example, height valuesmay be determined by a function (such as a logarithmic or sigmoidfunction) of the image values. As another embodiment, a map or look-uptable may be stored in the memory which maps image values to heightvalues. As a result, the method at 308 may including looking up andmapping each image value for each pixel to a corresponding height value.The resulting height values may be scalar values.

At 310, the method includes determining a gradient of the determinedheight values. As explained above with reference to FIG. 2, a gradientmay be calculated at each of the pixels of the 2D image. In oneembodiment, the processor of the ultrasound imaging system may calculatethe gradient of a pixel using the height value of that pixel and theadjacent pixels. Specifically, the gradient for each pixel may bedetermined according to a relationship or gradient equation (e.g.,Equation 1, as explained above with reference to FIG. 1) stored in amemory of the processor of the imaging system that takes into accountthe height value of the chosen pixel and the height values of thenearest (e.g., left and right) neighbors of the chosen pixel.Calculating the gradient includes calculating a normal of the surface ofthe pixel. In this way, a gradient surface normal may be determined foreach pixel of the 2D image.

After determining the gradient of the height values for each pixel, themethod continues to 312 to apply shading to the 2D image using thesurface normal of the determined gradient. The processor may calculateshading values for the pixels of the 2D image based on the gradientsurface normals. For example, the processor may make a logicaldetermination of the shading value for each pixel based on a shadingmodel stored in memory that is a function of the gradient surfacenormal. The processor may then apply the determined shading value to thepixel to form a shaded 2D image. As explained above with reference toFIG. 2, the shading model used to apply shading to the 2D image may beone or more standard shading models, such as a diffuse specular shadingmodel, a Phong reflection model, a Blinn-Phong shading model, a specularhighlight shading model, or the like. In alternate embodiments, theshading model may be a more complex global model which simulates lightpropagation with shadowing, and the like. The method at 312 may furtherinclude determining a color value for each pixel, according to colordata included in the acquired imaging data (e.g., in the case of Dopplerimaging). The color value (e.g., red or blue) may be based on adirection of flow, toward or away from the ultrasound probe. Thus, eachpixel may have a color value associated with it which is used to colorthe shaded 2D image. For example, the base color value for each pixel,without shading, may be taken from the original 2D image (generated fromthe acquired data, as described at 302) and used in the final shaded 2Dimage. As one example, each pixel may have a velocity value that isconverted (e.g., using a look-up table) to a resulting color value(e.g., red or blue). The color value is then shaded (e.g., brightnessmodulated) according to the normal of the gradient and the lightdirection.

In some embodiments, the gradient described above may also be used foredge enhancement and segmentation techniques that may then be applied tothe 2D ultrasound image.

At 314, the method includes displaying the shaded 2D image. As oneexample, displaying the shaded 2D image may include displaying the 2Dimage via a display device (such as display device 118 shown in FIG. 1).In this way, the resulting shaded 2D image may be presented to a user(such as a medical professional) via the display device. Examples of 2Dultrasound images shaded using a gradient determined from height valuescorrelated to ultrasound image data are shown in FIGS. 5 and 7, asdescribed further below.

FIGS. 4 and 5 show an example of a 2D Doppler ultrasound image that isgenerated using acquired image data that includes color data.Specifically, FIG. 4 shows an unshaded 2D Doppler ultrasound image 400,generated from an imaging dataset. The unshaded 2D Doppler ultrasoundimage 400 has not been shaded using the gradient surface shading methoddescribed herein (e.g., as described above with reference to FIGS. 2 and3). FIG. 5 shows a shaded 2D Doppler ultrasound image 500, generatedfrom the same imaging dataset as the unshaded 2D Doppler ultrasoundimage 400 of FIG. 4. However, the shaded 2D Doppler ultrasound image 500has been shaded using the gradient surface shading method describedherein (e.g., described above with reference to FIGS. 2 and 3). In FIG.5, only the colored portions of the shaded 2D Doppler ultrasound image500 (e.g., the pixels containing color data) have been shaded accordingto the gradient surface shading method described herein. Thus, thegrayscale portions of FIGS. 4 and 5 may look similar.

As seen in FIG. 4, the unshaded 2D Doppler ultrasound image 400 appearsrelatively flat with fuzzier edges (at the edge separating the color andgrayscale regions). However, the shaded colored regions of the shaded 2DDoppler ultrasound image 500, as seen in FIG. 5, appear crisper at theedges and give the image an appearance of depth (e.g., it looks lessflat and has increased contrast relative to the image 400 shown by FIG.4). Specifically, even though the shaded 2D Doppler ultrasound image 500is a 2D image generated from 2D image data (e.g., scalar image values),the resulting shaded image has a 3D appearance. As a result, a medicalprofessional may have an easier time recognizing 3D structures, andtherefore more complex structures, in the shaded 2D Doppler ultrasoundimage 500 as compared to the unshaded 2D Doppler ultrasound image 400.For example, color Doppler images of the fetal heart may be more easilyinterpreted and used for a more accurate patient diagnosis when theimages are shaded using the gradient surface shading method describedherein (e.g., using height values).

FIGS. 6 and 7 show an example of a 2D B-mode ultrasound image that isgenerated using acquired image data. Specifically, FIG. 6 shows anunshaded 2D B-mode ultrasound image 600, generated from an imagingdataset. The unshaded 2D B-mode ultrasound image 600 has not been shadedusing the gradient surface shading method described herein (e.g., asdescribed above with reference to FIGS. 2 and 3). FIG. 7 shows a shaded2D B-mode ultrasound image 700, generated from the same imaging datasetas the unshaded 2D B-mode ultrasound image 600 of FIG. 6. However, theshaded 2D B-mode ultrasound image 700 has been shaded using the gradientsurface shading method described herein (e.g., described above withreference to FIGS. 2 and 3). In FIG. 7, the entire shaded 2D B-modeultrasound image 700 have been shaded according to the gradient surfaceshading method described herein.

Similar to as described above with reference to FIGS. 4 and 5, theunshaded 2D B-mode ultrasound image 600 shown in FIG. 6 appearsrelatively flat with fuzzier edges while the shaded 2D B-mode ultrasoundimage 700, as seen in FIG. 7, appears crisper and gives the image anappearance of depth (e.g., it looks less flat and has increased contrastrelative to the image 600 shown by FIG. 6). Specifically, even thoughthe shaded 2D B-mode ultrasound image 700 is a 2D image generated from2D image data (e.g., scalar image values), the resulting shaded imagehas a 3D appearance. As a result, a medical professional may have aneasier time recognizing 3D structures, and therefore more complexstructures, in the shaded 2D B-mode ultrasound image 700 as compared tothe unshaded 2D B-mode ultrasound image 600.

In this way, 2D ultrasound images may be shaded using a gradientdetermined from height values that are correlated to image data (e.g.,scalar image values) of an imaging dataset acquired with a medicalimaging system. Shading 2D images in this way may produce 2D images thathave a 3D appearance and make complex structures more recognizable to aviewer/medical professional. As a result, these shaded 2D images may beeasier to use for diagnosis. Additionally, in the case of Dopplerultrasound images, the image data correlated to the height values fordetermining the gradient may include a power component of color Dopplerimage data. By utilizing the power component (as compared to using adifferent image value, such as intensity for B-mode images) for thisgradient shading technique, the resulting shaded images may be morecrisp and clear. For example, while the gradient shading techniquedescribed herein may be applied to other imaging modes, such as B-modeimages, the increased number of structures in B-mode images may make theresulting images less clear as compared to Doppler images. Thus, thegradient shading method described here may be advantageous for Dopplerimages. The technical effect of correlating image values of a datasetacquired with an ultrasound imaging system to height values, determininga gradient of the height values, applying shading to a 2D imagegenerated from the dataset using the determined gradient, and displayingthe shaded 2D image is producing a shaded 2D image that has a 3Dappearance and is therefore easier to diagnose with.

As one embodiment, a method comprises: correlating image values of adataset acquired with an ultrasound imaging system to height values;determining a gradient of the height values; applying shading to a 2Dimage generated from the dataset using the determined gradient; anddisplaying the shaded 2D image. In a first example of the method, thedataset includes color data. In a second example of the method, thedataset is a color Doppler dataset and the image values include a powercomponent from the color Doppler dataset. In a third example of themethod, the dataset is a B-mode dataset and the image values includeintensity values from the B-mode dataset. In one example, correlatingimage values to the height values includes, for each pixel of the 2Dimage generated from the dataset, converting an image value to acorresponding height value using a relationship between the image valueand the height value. Additionally, determining the gradient of theheight values may include determining a separate gradient for eachheight value of the height values, where each height value is associatedwith a corresponding pixel, and where the separate gradient for eachheight value is based on a difference between height values of pixelsadjacent to the corresponding pixel within the 2D image. Further, eachseparate gradient for each height value may include a surface normal,and applying shading to the 2D image may include applying shading to the2D image using the surface normal of each corresponding pixel of the 2Dimage.

In another example of the method, displaying the shaded 2D imageincludes displaying the shaded 2D image via a display screen of theultrasound imaging system. The method may further comprise accessing thedataset from a memory of the ultrasound imaging system. Additionally,the method may include filtering the image values prior to correlatingthe image values to height values and determining the gradient. In yetanother example, applying shading to the 2D image using the determinedgradient includes applying shading to the 2D image based on a shadingmodel which is a function of surface normals of the determined gradient,the shading model including one or more of a diffuse specular shadingmodel, a Phong reflection model, a Blinn-Phong shading model, and aspecular highlight shading model.

As another embodiment, a method comprises: accessing a dataset acquiredwith an ultrasound imaging system, the dataset including a powercomponent for each pixel of a 2D image generated from the dataset;interpreting the 2D image as a relief image by converting the powercomponent for each pixel to a height value; determining a gradient ofeach height value; shading the 2D image using a surface normal of eachdetermined gradient; and displaying the shaded 2D image. In one exampleof the method, shading the 2D image includes applying a shading model tothe 2D image using the surface normal of each determined gradient, wherethe shading model includes one or more of a diffuse specular shadingmodel, a Phong reflection model, a Blinn-Phong shading model, and aspecular highlight shading model. In another example of the method, thedataset includes color data and the ultrasound imaging system is a colorDoppler ultrasound imaging system. Additionally, converting the powercomponent for each pixel to a height value may include selecting pixelsof the 2D image that include color data and converting the powercomponent for each selected pixel to the height value. The method mayfurther include not shading pixels of the 2D image that do not containcolor data. The method may further include filtering the power componentof the selected pixels and converting the filtered power component ofeach selected pixel to the height value.

As yet another embodiment, an ultrasound imaging system comprises: anultrasound probe; a display device; and a processor communicativelyconnected to the ultrasound probe and display device and includinginstructions stored in memory for: accessing a dataset acquired with theultrasound probe from the memory; generating a 2D image from thedataset, where each pixel of the 2D image includes a power component;converting the power component of each pixel to a height value;determining a gradient surface normal for each height value; shading the2D image using the gradient surface normal; and displaying the shaded 2Dimage via the display device. In one example, the ultrasound imagingsystem is a color Doppler ultrasound imaging system. In another example,determining the gradient surface normal for each height value includes,for a selected pixel, determining the gradient surface normal for aheight value of the selected pixel using central differences and heightvalues of pixels adjacent to the selected pixel.

As used herein, an element or step recited in the singular and proceededwith the word “a” or “an” should be understood as not excluding pluralof said elements or steps, unless such exclusion is explicitly stated.Furthermore, references to “one embodiment” of the present invention arenot intended to be interpreted as excluding the existence of additionalembodiments that also incorporate the recited features. Moreover, unlessexplicitly stated to the contrary, embodiments “comprising,”“including,” or “having” an element or a plurality of elements having aparticular property may include additional such elements not having thatproperty. The terms “including” and “in which” are used as theplain-language equivalents of the respective terms “comprising” and“wherein.” Moreover, the terms “first,” “second,” and “third,” etc. areused merely as labels, and are not intended to impose numericalrequirements or a particular positional order on their objects.

This written description uses examples to disclose the invention,including the best mode, and also to enable a person of ordinary skillin the relevant art to practice the invention, including making andusing any devices or systems and performing any incorporated methods.The patentable scope of the invention is defined by the claims, and mayinclude other examples that occur to those of ordinary skill in the art.Such other examples are intended to be within the scope of the claims ifthey have structural elements that do not differ from the literallanguage of the claims, or if they include equivalent structuralelements with insubstantial differences from the literal languages ofthe claims.

1. A method, comprising: generating a flat, 2D image from a 2D datasetincluding scalar image values without height values, the 2D datasetacquired with an ultrasound imaging system; determining a gradient ofheight values from the scalar image values; applying shading to theflat, 2D image using the determined gradient; and displaying the shadedflat, 2D image, having a 3D appearance, via a display screen of theultrasound imaging system.
 2. The method of claim 1, wherein determiningthe gradient includes, for each pixel of the flat, 2D image generatedfrom the 2D dataset including the scalar image values, converting afirst scalar image value of the scalar image values included in the 2Ddataset to a corresponding height value using a relationship between thefirst scalar image value and the height value.
 3. The method of claim 2,wherein the relationship is one of a linear relationship or a monotonicfunction.
 4. The method of claim 2, where the height value represents aheight value of the first scalar image value but does not include heightdata.
 5. The method of claim 1, wherein determining the gradient of theheight values includes determining a separate gradient for each heightvalue of the height values, wherein each height value is associated witha corresponding pixel, and wherein the separate gradient for each heightvalue is based on a difference between height values of pixels adjacentto the corresponding pixel within the flat, 2D image.
 6. The method ofclaim 5, wherein each separate gradient for each height value is used tocompute a surface normal, and wherein applying shading to the flat, 2Dimage includes applying shading to the flat, 2D image using the surfacenormal of each corresponding pixel of the flat, 2D image.
 7. The methodof claim 1, further comprising accessing the 2D dataset from a memory ofthe ultrasound imaging system.
 8. The method of claim 1, furthercomprising filtering the scalar image values prior to determining thegradient.
 9. The method of claim 1, wherein applying shading to theflat, 2D image using the determined gradient includes applying shadingto the flat, 2D image based on a shading model which is a function ofsurface normals of the determined gradient, the shading model includingone or more of a diffuse specular shading model, a Phong reflectionmodel, a Blinn-Phong shading model, and a specular highlight shadingmodel.
 10. The method of claim 1, wherein the 2D dataset is a B-modedataset and the scalar image values include intensity values from theB-mode dataset.
 11. The method of claim 1, wherein the 2D dataset is acolor Doppler dataset and the scalar image values are only a powercomponent from the color Doppler dataset.
 12. The method of claim 11,wherein the color Doppler dataset further includes a velocity value foreach pixel of the flat, 2D image, each velocity value converted to acolor value, and wherein shading the flat, 2D image includes shading thecolor value of each pixel of the flat, 2D image using the determinedgradient.
 13. An ultrasound imaging system, comprising: an ultrasoundprobe; a display device; and a processor communicatively connected tothe ultrasound probe and the display device and including instructionsstored in memory that, when executed during operation of the ultrasoundimaging system, cause the processor to: access a 2D dataset, includingonly 2D scalar data and no 3D data, acquired with the ultrasound probefrom the memory; generate a flat, 2D image from the 2D dataset, whereeach pixel of the flat, 2D image includes a scalar, image value; convertthe scalar, image value of each pixel to a scalar, height value via ascalar valued function; determine a gradient surface normal for eachscalar, height value; shade one or more pixels of the flat, 2D imageusing the gradient surface normal; and display the shaded flat, 2D imagevia the display device.
 14. The ultrasound imaging system of claim 13,wherein determining the gradient surface normal for each scalar, heightvalue includes, for a selected pixel, determining the gradient surfacenormal for the scalar, height value of the selected pixel using centraldifferences and scalar, height values of pixels adjacent to the selectedpixel.
 15. The ultrasound imaging system of claim 13, wherein the 2Ddataset is a B-mode dataset and the scalar, image value of each pixel isan intensity value from the B-mode dataset.
 16. A method, comprising:generating a flat, 2D image from a 2D, B-mode dataset including scalarintensity values without height values, the 2D, B-mode dataset acquiredwith an ultrasound imaging system; determining a gradient of heightvalues from the scalar image values by, for each pixel of the flat, 2Dimage, converting a first scalar intensity value of the scalar intensityvalues included in the 2D, B-mode dataset to a corresponding heightvalue using a relationship between the first scalar intensity value andthe height value; applying shading to the flat, 2D image using thedetermined gradient; and displaying the shaded flat, 2D image, having a3D appearance, via a display screen of the ultrasound imaging system.17. The method of claim 16, wherein the relationship is one of a linearrelationship or a monotonic function.
 18. The method of claim 16, wherethe height value represents a height value of the first scalar intensityvalue but does not include height data.
 19. The method of claim 16,wherein determining the gradient of the height values includesdetermining a separate gradient for each height value of the heightvalues, wherein each height value is associated with a correspondingpixel, and wherein the separate gradient for each height value is basedon a difference between height values of pixels adjacent to thecorresponding pixel within the flat, 2D image.
 20. The method of claim19, wherein each separate gradient for each height value is used tocompute a surface normal, and wherein applying shading to the flat, 2Dimage includes applying shading to the flat, 2D image using the surfacenormal of each corresponding pixel of the flat, 2D image.